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Advanced topic 9, 2012
User-Centric Management of Wireless LANs The content of this wiki page was adapted from the paper above. All credit goes to original authors. Topic 9 from Advanced Topics 2012 PART 2 Overview of NM in WLANs Basic management entities and activities There are three main management entities defined in IEEE 802.11 family standards: *Entities: ** Station management (SME) ** MAC Sub-layer Management Entity (MLME) **Physical Layer Management Entity (PLME) The dominant functions of MLME and PLME are to in-phase, managing power, combination and recombination, which is usually used to process latency in network device firmware, being more suitable to be executed in hardware instead of network management. SEM is to gather the inter-layers status and to configure specific parameters. It is the central entity in network management. Meanwhile, MLME and PLME provide some system status to SME by interfaces between MLME and SME. There are also three activities of APs: *Activities: *Parameter configuration *Users information management *Network monitoring Specifically, parameter configuration includes channel selection and power configuration; user information management contains AP association lists and management; and network monitoring relates to both downlink and uplink monitoring traffic from users to APs. Moreover, there are two types among those activities. Passive activities include the priority management and the network monitoring while positive activities include the parameter configuration and the AP association lists. Additionally, during network deployment, power configuration can be set without much change to it. Therefore, the scope of AP association and channel selection is critical when it comes to most parts of network management. AP Association and Channel Selection Firstly, see the Fig. 1 showing the basic working flow over the network management framework in traditional WLANs. AS can be seen from the figure, an AP needs to select a channel either manually or via the configuration of neighboring APs within sensing coverage. Then, configuration information will be sent in the beacon frames to those users nearby. However, the user is more likely to only select the AP from those access points with enough signal power even if this user can sense and know the signal power in all the transmissions within the sensing coverage. In the last step, the AP adds the user into its serving list based on whether the user is admitted with secure credentials like the permissible MAC address. Furthermore, the AP association and the channel selection doesn't use AP-related or user-related information, so they tend to be AP-centric. PART 2 User-centric network management framework The fundamental idea of user-centric network management framework, instead of traditional AP-centric network management framework, is to involve the users participation in network management framework. This framework can solve the throughput problems AP-association left. The basic principle is to provide the pipeline information exchange platform and duplexing selection between APs and users that enable to enhance traditional APs one-side control to consider what a user needs. The detailed user-centric network management working procedures illustrate below. First of all, AP selects a channel manually or based on neighboring APs’ sensing range. After that, AP delivers configuration information (like channel, data rate, and MAC address) periodically to users by beacon within its sensing range. The user, collecting the APs status within its receiving range periodically, considers the network conditions (like beacon frame transmission and data transmission) which is also as network snapshot and piggybacks the network snapshot, access priority and association request frame to all candidate APs in its receiving range. AP, which receives the frame, calculates the potential throughput for users by users provided information and transmission status by itself and returns the response frame with calculated results to the users by piggyback. Then the user will choose the AP that provides the maximum potential throughput and inform it with a new association request. The selected AP replies with a response frame to finalize the association and stores the users’ network snapshot. It is worthy mentioning that AP not only can provide the potential throughput and be selected by users but also can dynamically select the operational channel and optimize the aggregate throughput by the collected user information and snapshot under user-centric network management system. Moreover, users can select the AP that can provide the maximum throughput, avoiding being passive selected by AP. PART 3 Theoretical Analysis The theoretical analysis is introduced to illustrate why the user-centric network management framework is the superior approach than the traditional network management framework in AP association and channel selection. Because the performance of p-persistent access model is very similar to the IEEE 802.11MAC contention access mechanism, the former is used to simulate the performance of the latter. In this paper, the downlink traffic is the unique considered in the analysis since the traffic on downlink takes the most percentage of the total network traffic. This section is divided into three parts which are the system model, optimal AP association and the optimal channel selection. A. System model Firstly, the system model is illustrated as follow. In order to calculate the throughput some fundamental knowledge about this system should be briefly introduced. In this paper, the failed transmissions are only affected by the packet collisions while the impact of other transmission effects is not considered. According to CSMA mechanism, if more than one accessed points existed in the sensing area and transmit simultaneously, the transmission of packet would be fail. In other words, only one AP is allowed to transmission in the same sensing range. Hence, the probability of a successful transmission from ���� to ���� in a time slot which is operating on channel �� is given by: http://dx.doi.org/10.1109/TNSM.2011.072611.100031 (1) Where, ���� denote the probability of the transmission of AP ���� in a time slot, and ������ denote the probability that ���� sends packets to ���� in a time slot. Hence, the probability that user ���� senses channel �� busy is obtained by: (2) Therefore, the throughput can be defined as the average payload size transmitted in a unit time when ���� links with ���� and operates on channel ��. The formula of the throughput is given by: (3) Where, E�� indicates the average payload size of a data packet, and ��busy and ��idle denote the average length of a busy time slot and an idle time slot, respectively. Substituting (1) and (2) into (3), the formula of the throughput is obtained as: (4) Where, there is a relationship between ������ and these parameters which are ����, the number of users linked with ����, the traffic load of each user, and the priority of each user. This relationship is derived as follows. The access queue for each priority or each user in downlink transmission is usually maintained by the associated AP which allocates each user with an independent queue. There are two virtual contention mechanisms utilized in the queues to share the physical radio which are Distributed Coordination Function (DCF) and Enhanced DCF (EDCF). The fundamental concept about these two mechanisms is shown below. Under the virtual contention mechanism of DCF, a user selects a backoff window from ����min, where ����min denotes the minimum contention window. The packet is transmitted when the back-off window reduces to zero. If the packet transmission is fail because of the contention, the user randomly chooses a new back-off window from a double extended range 2����min until the contention window achieves the maximum contention window ����max. If the successful packet transmission is recovered, the contention window returns to ����min immediately. If the EDCF is used as the virtual contention mechanism, the process is different with that with DCF. The different minimum and maximum contention windows have different priorities under the EDCF mechanism. The level of the priority is inverse to the values of the minimum and maximum contention windows. The transmit probability of the queue for user ���� with EDCF can be obtained as: (5) Where, �������� stands for the average contention window for the access queue to user ��j. ������ indicates the load of the queue for user ���� associated with AP ����. The transmit probabilities are different with different virtual contention mechanism. Firstly, because the priorities of all the users under the IEEE 802.11 DCF are the same, the CWij are all the same to all queues. Therefore, the transmit probability under this situation is given by: (6) Where, (7) Secondly, if the users under IEEE 802.11e EDCF virtual contention mechanism, the queues with different priorities have different minimum and maximum contention windows, which results that the average contention windows is different. �������� is given by: (8) Where, Substitute (8) into (7), the pi,c can be obtained when ����, http://dx.doi.org/10.1109/TNSM.2011.072611.100031 and are given. Substitute (8) into (5), the value of pij can be obtained. These analytical results are very useful to make a design on the optimal AP association and the optimal channel selection. B. Optimal AP Association In the second section, the optimal AP association is discussed. As the description before, AP association is implemented when a new user joins the network or handoff because the previous AP is unable to achieve the performance requirement. The optimal AP association corresponding to the AP would provide the maximum throughput to a user. The mathematical model of the throughput is given by: (9) substituting (4) into (9): (10) From the formula (10), the throughput may fluctuate with neighbors’ network conditions and the transmission probability ������. Hence, the information pipeline under the user-centric framework becomes significant important on the optimal AP association. The neighbors’ network conditions under the traditional network management framework are usually available. Therefore, the throughput for user ���� is obtained as: (11) However, this throughput level is not the optimal. C. Optimal Channel Selection The third section demonstrates the Optimal Channel Selection. In the traditional network management framework, only the transmit probability pij of the AP is available for channel selection. Hence, the channel selection is based on the network load of neighboring APs, which is proportion to pij. Compared to the traditional network management framework, AP under the user-centric framework is able to collect the network condition by the associated users. The optimal channels could be able to be selected to maximize the aggregate throughput. The aggregate throughput for AP under the user-centric framework is given by: (12) Therefore, it is impossible for the traditional network management framework to achieve the maximum total throughput by channel selection since the situation that the sensing areas of the access point and the user linked to it change with different locations does not always hold. However, the user-centric framework is able to dynamically collect the network conditions to achieve the optimal channel selection and obtain the maximum aggregate throughput. Implementing the Management Framework The dual-threshold triggering conditions A new association between AP and user triggered by users only when the existing association throughput is lower than a lower-bound threshold or a new (optimal) AP-association potential throughput is much stronger than its current throughput by at least a minimum improvement threshold. Specifically, the user executes a new AP association procedure only if: A new association triggered by AP happens only when the current aggregate downlink throughput is lower than a lower-bound threshold or a new (optimal) channel selection potential throughput is much stronger than its current throughput by at least a minimum improvement threshold . Specifically, AP establishes a new AP association procedure only if: The dual period operation AP association or channel selection should be taken place periodically to constantly optimize to such operation. Then a comparatively short T is selected in order to have an initialization period during each Ta procedure, and users who have been connected to the AP need to recalculate the throughput that may be potentials to them. Since the operation of channel selection will lead to the reconnection of all connected users, select a longer Tc (decision period) rather than Ta (shorter period), like the previous procedure, the AP assesses its general performance and determines whether to set a new channel selection. At last, �� ∈ (0, 1) and �� ∈ (0, 1) acted as the smoothing factors, depending on the realistic considerations can be introduced to get the average traffic ups and downs: Where，�� and �� normally are set to 0.9. Additionally, ������, and ������,��+���� stand for updated throughput of ���� at time t and the average throughput in the time range [��, �� + ����) respectively, which can be used to define ����,�� and ����,��+���� as well. The throughput of the APs and the connected users should be updated at each instant decision time and see if the triggering conditions are satisfied, then the finest channel selection described above can be used. However, even though the short period of update intervals can result in more throughput, hard breakdowns caused from each recombining period in transmission will affect users because of the high frequency in recombining. The effect on hard breakdowns has to be assessed through specifying a WLAN APs, in order to analyze the simulated deployment and then get the value for ���� = 600s and ���� = 1800s. Obviously, the lower-bound can be set as follows since the choice of it is in linear proportion to the average throughput: Hence, it can be seen that the calculation depends on the link transmission speed ® and the number of users (Nu). And CR∈ (0, 1) is a mapping coefficient, while NA is the number of APs. For example, if R = 54 Mbps, then set CR = 0.5. Meanwhile, thresholds are improved aimed at enlarging the throughput and the choice of the enhanced thresholds will be determined by the period time of breakdown. Here, set these thresholds as follows for later simulations: Where Tb stands for the breakdown period and C is a constant which is always larger than 1, determining the improved extension. PART 6 Simulations In order to analyze the throughput performance of our purposed user-centric network management framework, the author uses the software NS2 to do the simulations. The parameters can be seen blow : All the APs and users are randomly and uniformly distributed with density 1AP per unit area , while the user density varies with the simulation senarios. A : Effect of Access Priority This senario is : one AP serves 8 users. The downlink throughput is measured of one user in different priorities. The available through of the user with high access priority is always greater than that with low access priority. And the available throughput for the considered user decreases with the number of users with high priority no matter what access priority it has. Access priority distribution in the AP affects the potential through, and since the throughput decreases as the number of users increases,the AP association can play a vital role in increasing the throughput for a user. B : AP Association over User-centric Network Management Framework This case is: there are always data packets to transmit on all the queues of all APs. One user is “tagged” as the observing user and we fix the AP association of all other users. We evaluated three types of management frameworks: one is AP selection under the traditional management framework, the second is optimal selection in AP-centric framework and the last is user-centric management framework. It is obversed that AP association based on the usercentric network management framework always outperforms other frameworks, and the throughput gain compared to ranges from 25''.0% to 90.5%. The throughput comes from access priority and the network conditon. It's possible that the current AP has a lot of users with high priority. Then, a new AP association with less high priority users will probide better throughput for that uses. Again, if the network condition of the current AP is poor(e.g. high noise or fading) resulting in poor throughput, the throughput can be increased by associating with a new AP with better network condition. C :Channel Selection over User-centric Network Management Framework Next, we investigate the effect of the channel selection on the total throughput of users associated with one AP. We fix the user density to 2users per unit area area, and take one AP as observing AP which associates with two observing users. User-centric management provides highest throughput -max 69.3%, while as the APs get saturated with load, the throughput becomes similar for all the system. * Channel selection in user-centric management framework is initiated by the AP. If the channel condition is poor, than the AP decides to change the channel to a potentially better channel. The channel can give poor throughput for several reason-channel selective fading of channel collision with neighboring AP are some of the reason. We can see that we can get more throughput from user-centric management, with a maximum gain of 69.3%. However, as the APs get saturated with users, the throughput performances for all the management systems become similar as all the paths are full. D : Impact of Dual-threshold in Implementation Finally, we explore the impact of dual-threshold for triggering management operations on user throughput. we get that the value of the dual-threshold depends on the setting of ���� and ��. We have the same simulationscenario as Section VI-B to explore the impact of dualthreshold on user throughput. The user density is fixed to 2 users per unit area, and the target user is configured as highpriority user. Here, CR∈ (0, ''1) is a mapping factor for available lower-bound throughput and physical transmitting speed C>1 is a constant for leveraging the improvement The throughput increases as CR increases. This happens because if the lower bound threshold is small it won't trigger the management operation. So throughput will not increase. AND, the throughput decreases as C increases. This is because a large value of minimum improvement threshold will also hinder the execution of management operation. * *